The technologies for enhancing the sound quality of a speech signal generated in a noisy environment have numerous application fields, and have been actively studied until now as a research field having enormous potential value.
The application fields of a sound quality enhancing technology include, for example, speech coding, teleconference, hands-free mobile telephony, hearing aids, speech recognition, etc. The sound quality of a speech and the recognition characteristic for clarity of a human being tend to depend on the magnitude of a spectrum for a short time and are relatively insensible to the phase of a speech signal. Based on the characteristics, the current sound quality enhancing technology has focused on suppressing noise added to a speech signal.
As described above, the conventional technology is mainly intended to improve the sound quality of a noisy speech for speech communication, and thus causes the improved speech to be distorted. Although the distortion hampers further enhancement in the performance of speech recognition, many speech recognition systems employ such technology. Such a conventional technology is based on a Wiener filter or a Kalman filter and is effective in removing static noise, but is more vulnerable to distortion when it faces more noise and can not cope with dynamic noise.
Therefore, in the conventional noise reduction method that operates in this way, distortion is caused when improving sound quality and improvement of sound quality is not directly connected to the performance of speech recognition.
Further, the conventional single channel noise processing technology is effective in removing static noise but has a limit in removing dynamic noise whose characteristic varies over time.